Day 2 :
The Institution of Engineers (IEI), India
Keynote: Understanding cancer through microbial adherence, toxin liberation and oncogenes: A relation of cytokines and macrophage
Time : 10:00 - 10:40
Nitosh Kumar Brahma a life Fellow of The Institution of Engineers, India. He is actively engaged as Convener of WBSC/IEI, Chemical Engineering Division and as Visiting Professor of Institute of Genetic Engineering (IGE) Badu, Madhamgram. He completed his double Graduation with Distinction; BSc ÇU, B Tech, M Tech, TUB and Doctoral work in Max-Planck Germany 1968-1986. He published more than 100 articles related to Genetic Engineering, Chemical and Bio-Chemical Process Technology. He is the author of three books entitled Introduction to Chemical Science and Engineering, Molecular and Engineering Concepts of Micro-Biology and Bacterial adherence.
Causing cancer and its remedy in presence of microbes has been reported. Human healthy body contains10 trillion good immunological active cells and 100 trillion gut microbes. They are managing the metabolic and defense mechanisms. Symbiotically and infectiously microbes of a human body are managing the immunological tolerances. A tumor cell is differentiated by benign and malignancies (metastases). The disorders if caused by genetic mutations caused due to hereditary and environmental effects, may initiate cancer growth. Environmental factors are characterized by sudden effects of radiations and chemical reactions. A galaxy is conceptualized by gathering of millions of milk ways with trillions of planetary systems, symbolized the unending concepts of galaxy by Stephan Hawkins Black Hole and Einsteins Relativity and E=mc2 relations. Similarly, the 100 trillion bacterial cells in a healthy body increased trillion-time possibilities to generate a cancer cell and its settlement on a surface of epithelial cells and are not destroyed by macrophage. In a healthy body.106x103x103x10/106x106x102=1/10=0.1=10% possibilities may initiate a generation of a cancer cell, due to inactivity of good lymphocytes and the generation of pathogenic microbes, prone to adhere and proliferate on thin epithelial cell liberates exo- and endo- toxins to destroy immune resistance. A cancer cell is adherence prone toxin liberating multidirectional cellular proliferation. Chemo- and radiotherapy are approached for treatments and need target-oriented drug delivery. Due to chemo, the tolerance factor and the immunological responses are also reduced, subsequently the existing of 1014 bacterial cells Camouflaging them as good microbes may change rapidly by genetic transformation to pathogen, opportunistic infections, initiate cancer patients towards fatal death by multiorgan failures. We are all generating cancer cells, continuously and are being destroyed by our immune system. In case of immune deficiencies this process could be stopped and could generate metastases. Louise Pasture, unpredictable power of microbes is well established in case of AIDS, for T-cell damage and aberration of chromosome 17 in case of Leukemia symbolize the shifting of immunological tolerance towards immune deficiencies and suppressions. During antibiotic and chemotherapy, antibiotic resistant as caused by transposable elements may lead to resistant bacterial proliferation and the damage of salt Na+, K+ balance. Lung, colon and pancreas, are those sustainable organs. So bidirectional chemotherapy of BNT, genetically engineered hybrid Escherichia coli could be appropriate to activate cytokine and macrophages and are characterized by the binding power of [Ab]+[Ag]à[AbAg]àimmune complex (Figure.4). Cancer causing bacterial involvements varied by groups A, B and C and their probabilistic influence on organ specific cancer.
Cedar Hospital, India
Time : 10:40-11:20
Rajesh Ravindran Nair is working at Cedar Hospital, India.
Artificial intelligence (AI) is a term for simulated intelligence in machines. These machines are programmed to "think" like a human and mimic the way a person act. The goals of artificial intelligence include learning, reasoning and perception and machines are wired using a cross-disciplinary approach based in mathematics, computer science, linguistics, psychology and more. Since its beginning, artificial intelligence has come under scrutiny from scientists and the public alike. One common theme is the idea that machines will become so highly developed that humans will not be able to keep up and they will take off on their own, redesigning themselves at an exponential rate. Another is that machines can hack into people's privacy and even be weaponized. Other arguments debate the ethics of artificial intelligence and whether or not intelligent systems such as robots should be treated with the same rights as humans. Artificial intelligence (AI) has been springing up in hospitals and clinics around the world in both research and direct patient care settings, with machine learning being used to predict patient outcomes, diagnose diseases, and suggest treatments. In the field of oncology, emerging AI technologies can detect tumors, diagnose cancers, and even generate chemotherapy treatment recommendations that adjust in real time based on patient responses. Google's AI algorithm can detect cancer metastases with 92% accuracy. Google's AI software encompasses a variety of healthcare functions, from predicting the amount of time a patient will spend in the hospital to their probability of being readmitted, and even assessing their risk for death. In addition to rapidly sifting through extensive medical records to assess these metrics, Google's AI has a variety of pathologic functions. Detecting diabetic eye disease, expanding genomic research, and using digital pathology for cancer detection are among the most prominent applications. Google's AI cancer detection capabilities were published in a paper titled "Detecting Cancer Metastases on Gigapixel Pathology Images.” A convolutional neural network, a method that involves computers making predictions based on recognizing visual patterns, was used to detect tumors as small as 100 × 100 pixels, with an accuracy of 92.4%. This is compared with the previous most accurate AI method, which had a tumor detection accuracy of 82.7%, whereas pathologists conducting their own manual search had an accuracy of 73.2%. Models are trained through generating heat maps that display the probability of tumor locations, with the maximum value representing the most probable tumor location. This method reduces the false-negative rate of tumor detection by 25% compared with pathologists and by 50% compared with the previous best AI method. Most errors made by Google's AI in tumor detection were related to the method of tissue preparation, primarily out-of-focus slides of tissues, which could be mitigated through more comprehensive labels for varying tissue types and improved scanning quality. Although Google's AI has the potential to improve the accuracy of cancer detection, further improvements in the technology are necessary in order to ensure that it is equipped for larger data sets.